Detection of fossil fuel emission trends in the presence of natural carbon cycle variability
Atmospheric CO _2 observations have the potential to monitor regional fossil fuel emission (FFCO _2 ) changes to support carbon mitigation efforts such as the Paris Accord, but they must contend with the confounding impacts of the natural carbon cycle. Here, we quantify trend detection time and magn...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2019-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ab2dd7 |
| _version_ | 1797748001130676224 |
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| author | Yi Yin Kevin Bowman A Anthony Bloom John Worden |
| author_facet | Yi Yin Kevin Bowman A Anthony Bloom John Worden |
| author_sort | Yi Yin |
| collection | DOAJ |
| description | Atmospheric CO _2 observations have the potential to monitor regional fossil fuel emission (FFCO _2 ) changes to support carbon mitigation efforts such as the Paris Accord, but they must contend with the confounding impacts of the natural carbon cycle. Here, we quantify trend detection time and magnitude in gridded total CO _2 fluxes—the sum of FFCO _2 and natural carbon fluxes—under an idealized assumption that monthly total CO _2 fluxes can be perfectly resolved at a 2°×2° resolution. Using Coupled Model Intercomparison Project 5 (CMIP5) ‘business-as-usual’ emission scenarios to represent FFCO _2 and simulated net biome exchange (NBE) to represent natural carbon fluxes, we find that trend detection time for the total CO _2 fluxes at such a resolution has a median of 10 years across the globe, with significant spatial variability depending on FFCO _2 magnitude and NBE variability. Differences between trends in the total CO _2 fluxes and the underlying FFCO _2 component highlight the role of natural carbon cycle variability in modulating regional detection of FFCO _2 emission trends using CO _2 observations alone, particularly in the tropics and subtropics where mega-cities with large populations are developing rapidly. Using CO _2 estimates alone at such a spatiotemporal resolution can only quantify fossil fuel trends in a few places—mostly limited to arid regions. For instance, in the Middle East, FFCO _2 can explain more than 75% of the total CO _2 trends in ∼70% of the grids, but only ∼20% of grids in China can meet such criteria. Only a third of the 25 megacities we analyze here show total CO _2 trends that are primarily explained (>75%) by FFCO _2 . Our analysis provides a theoretical baseline at a global scale for the design of regional FFCO _2 monitoring networks and underscores the importance of estimating biospheric interannual variability to improve the accuracy of FFCO _2 trend monitoring. We envision that this can be achieved with a fully integrated carbon cycle assimilation system with explicit constraints on FFCO _2 and NBE, respectively. |
| first_indexed | 2024-03-12T15:58:40Z |
| format | Article |
| id | doaj.art-790b0c4245f9495c900bd141ad8e064e |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:58:40Z |
| publishDate | 2019-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-790b0c4245f9495c900bd141ad8e064e2023-08-09T14:44:30ZengIOP PublishingEnvironmental Research Letters1748-93262019-01-0114808405010.1088/1748-9326/ab2dd7Detection of fossil fuel emission trends in the presence of natural carbon cycle variabilityYi Yin0https://orcid.org/0000-0003-4750-4997Kevin Bowman1https://orcid.org/0000-0002-8659-1117A Anthony Bloom2John Worden3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States of America; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, United States of AmericaJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States of America; Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, United States of AmericaJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States of AmericaJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States of AmericaAtmospheric CO _2 observations have the potential to monitor regional fossil fuel emission (FFCO _2 ) changes to support carbon mitigation efforts such as the Paris Accord, but they must contend with the confounding impacts of the natural carbon cycle. Here, we quantify trend detection time and magnitude in gridded total CO _2 fluxes—the sum of FFCO _2 and natural carbon fluxes—under an idealized assumption that monthly total CO _2 fluxes can be perfectly resolved at a 2°×2° resolution. Using Coupled Model Intercomparison Project 5 (CMIP5) ‘business-as-usual’ emission scenarios to represent FFCO _2 and simulated net biome exchange (NBE) to represent natural carbon fluxes, we find that trend detection time for the total CO _2 fluxes at such a resolution has a median of 10 years across the globe, with significant spatial variability depending on FFCO _2 magnitude and NBE variability. Differences between trends in the total CO _2 fluxes and the underlying FFCO _2 component highlight the role of natural carbon cycle variability in modulating regional detection of FFCO _2 emission trends using CO _2 observations alone, particularly in the tropics and subtropics where mega-cities with large populations are developing rapidly. Using CO _2 estimates alone at such a spatiotemporal resolution can only quantify fossil fuel trends in a few places—mostly limited to arid regions. For instance, in the Middle East, FFCO _2 can explain more than 75% of the total CO _2 trends in ∼70% of the grids, but only ∼20% of grids in China can meet such criteria. Only a third of the 25 megacities we analyze here show total CO _2 trends that are primarily explained (>75%) by FFCO _2 . Our analysis provides a theoretical baseline at a global scale for the design of regional FFCO _2 monitoring networks and underscores the importance of estimating biospheric interannual variability to improve the accuracy of FFCO _2 trend monitoring. We envision that this can be achieved with a fully integrated carbon cycle assimilation system with explicit constraints on FFCO _2 and NBE, respectively.https://doi.org/10.1088/1748-9326/ab2dd7fossil fuel emissionstrend detectionCO2 monitorcarbon cycle |
| spellingShingle | Yi Yin Kevin Bowman A Anthony Bloom John Worden Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Environmental Research Letters fossil fuel emissions trend detection CO2 monitor carbon cycle |
| title | Detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| title_full | Detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| title_fullStr | Detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| title_full_unstemmed | Detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| title_short | Detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| title_sort | detection of fossil fuel emission trends in the presence of natural carbon cycle variability |
| topic | fossil fuel emissions trend detection CO2 monitor carbon cycle |
| url | https://doi.org/10.1088/1748-9326/ab2dd7 |
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